Senior Software Engineer at Target

Developed Python-based FastAPI backend services supporting retail data workflows, improving API response latency by ~26% through optimized async processing. Built and integrated RAG-based pipelines using vector databases to enable personalized product recommendations and improve search relevance. Implemented LLM-powered workflows using modern NLP techniques to enhance real-time user interaction and personalization. Designed and optimized data pipelines using Pandas and Spark for improved analytics efficiency, integrated backends with REST and GraphQL APIs, and implemented Kafka event-driven pipelines for real-time distributed processing. Improved observability by integrating Prometheus, Grafana, and ELK to detect pipeline failures faster. Strengthened authentication/authorization using OAuth2 and JWT. Contributed to containerized deployments using Docker and Kubernetes.

Senior Software Engineer at Walmart

Built scalable Python backend systems (Flask/Django) supporting large-scale e-commerce data processing workflows. Developed machine learning models using TensorFlow and scikit-learn to improve product recommendation accuracy. Designed and maintained ETL pipelines using Airflow and Spark, reducing processing time by ~30%. Implemented vector search systems using FAISS/Elasticsearch to improve relevance and response speed, and optimized data storage/retrieval using PostgreSQL and Redis to reduce query latency. Integrated LLM-based features into backend workflows to enhance personalization and user experience, and improved reliability with error handling and retry strategies. Supported AWS-based deployments (S3, Lambda) and collaborated on end-to-end data flows to ensure consistency across analytics and user-facing systems.